lib/dnn/core/layers/embedding.rb in ruby-dnn-0.16.2 vs lib/dnn/core/layers/embedding.rb in ruby-dnn-1.0.0

@@ -1,9 +1,11 @@
 module DNN
   module Layers
 
     class Embedding < TrainableLayer
+      include LayerNode
+
       attr_reader :input_length
       attr_reader :weight
       attr_reader :weight_initializer
       attr_reader :weight_regularizer
 
@@ -20,17 +22,12 @@
         @weight_initializer = weight_initializer
         @weight_regularizer = weight_regularizer
         @weight = Param.new(nil, Xumo::SFloat[0])
       end
 
-      def call(input_tensor)
-        build(@input_shape) unless built?
-        Tensor.new(forward_node(input_tensor.data), Link.new(nil, self))
-      end
-
       def build(input_shape)
-        @built = true
+        super(@input_shape)
         @weight.data = Xumo::SFloat.new(@input_length)
         @weight_initializer.init_param(self, @weight)
         @weight_regularizer.param = @weight if @weight_regularizer
       end
 
@@ -53,27 +50,9 @@
         nil
       end
 
       def regularizers
         @weight_regularizer ? [@weight_regularizer] : []
-      end
-
-      def to_proc
-        method(:call).to_proc
-      end
-
-      def >>(layer)
-        if RUBY_VERSION < "2.6.0"
-          raise DNN_Error, "Function composition is not supported before ruby version 2.6.0."
-        end
-        to_proc >> layer
-      end
-
-      def <<(layer)
-        if RUBY_VERSION < "2.6.0"
-          raise DNN_Error, "Function composition is not supported before ruby version 2.6.0."
-        end
-        to_proc << layer
       end
 
       def to_hash
         super(input_shape: @input_shape, input_length: @input_length,
               weight_initializer: @weight_initializer.to_hash, weight_regularizer: @weight_regularizer&.to_hash)